The easiest way to perform a cross join in R is to use the crossing() function from the tidyr package:
library(tidyr) #perform cross join on df1 and df2 crossing(df1, df2)
The following example shows how to use this function in practice.
Example: Perform Cross Join in R
Suppose we have the following two data frames in R:
#define first data frame df1 = data.frame(team1=c('A', 'B', 'C', 'D'), points=c(18, 22, 19, 14)) df1 team1 points 1 A 18 2 B 22 3 C 19 4 D 14 #define second data frame df2 = data.frame(team2=c('A', 'B', 'F'), assists=c(4, 9, 8)) df2 team2 assists 1 A 4 2 B 9 3 F 8
We can use the crossing() function from the tidyr package to perform a cross join on these two data frames:
library(tidyr) #perform cross join cross <- crossing(df1, df2) #view result cross # A tibble: 12 x 4 team1 points team2 assists 1 A 18 A 4 2 A 18 B 9 3 A 18 F 8 4 B 22 A 4 5 B 22 B 9 6 B 22 F 8 7 C 19 A 4 8 C 19 B 9 9 C 19 F 8 10 D 14 A 4 11 D 14 B 9 12 D 14 F 8
The result is a data frame that contains every possible combination of rows from each data frame.
For example, the first row of the first data frame contains team A and 18 points. This row is matched with every single row in the second data frame.
Next, the second row of the first data frame contains team B and 22 points. This row is also matched with every single row in the second data frame.
The end result is a data frame with 12 rows.
The following tutorials explain how to perform other common operations in R:
How to Do a Left Join in R
How to Do a Right Join in R
How to Do an Inner Join in R